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Interactivity in smart environments

  • Number of credits 7.5 credits

About the course

The course is divided into a theoretical part (4,5 ECT) and a practical part (3 ECT). The theoretical part covers theoretical frameworks and methods for developing and evaluating intelligent interactive systems and provides introduction into how using these in practice. Parts of the content in the theoretical part are applied in the practical part, which is conducted in parallel, and that consists of a group project.

The main theme of the course is theories, methods and technologies for the development of future intelligent interactive environments where humans and proactive, reactive, autonomous and social software agents communicate and cooperate to reach goals. Sometimes the software agents are embedded in robotic systems or in other artefacts/materials in the physical environment. The student will acquire knowledge about main research themes and experimental practices in the field of intelligent interactive environments as well as develop her/his skills in constructing and evaluating intelligent interactive environments. Different paradigms will be introduced and discussed, primarily from an interaction and  design perspective such as ubiquitous computing, ambient intelligence, augmented and virtual reality, intelligent and adaptive user interfaces, tangible interfaces, persuasive technology, decision-support systems, Internet of Things and people, smart homes, semi-autonomous systems, social norms and agent societies.

Different societal challenges will be addressed through cross-disciplinary collaboration in student projects. In the laboratory part of the course theories, methods and techniques discussed in the theoretical part are put into practice. From a societal perspective, the aim may be designing for empowerment, increasing autonomy, safety, competence, cohesion, social inclusion, relatedness, motivation and behaviour change in people; from a technology perspective the aim may be designing the interactivity by integrating self-learning, self-adaptation, sensor networks, semi-autonomous multi-agent systems, intelligent user interfaces, etc. that are instrumental for reaching the societal aims and meeting the individual’s preferences and needs.

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Course is given by
Department of Computing Science